Abstract Antibiotic resistance has emerged as a global threat. Many argue that we have reached a post-antibiotic era, when simple bacterial infections could result in devastating consequences. To address this crisis, extensive efforts are needed to develop strategies to better use existing antibiotics, in addition to developing new ones. In particular, it is critical to understand how bacterial populations respond to antibiotic treatment and how antibiotic treatment can modulate the generation and spread of antibiotic-resistant bacteria. A major mechanism of rapid spread of antibiotic resistance is horizontal gene transfer (HGT), especially conjugation. We recently showed that in a broad range of conjugative systems antibiotics determine conjugation dynamics primarily by serving as a selective driver. In particular, antibiotics can both promote and suppress HGT dynamics, depending on how antibiotics affect growth rates of populations undergoing conjugation. Based on these results, the central goal of the proposed research is to examine in depth how antibiotic treatment can be applied to minimize the spread of antibiotic resistance genes or to force the reversal of the resistance once it was acquired. To achieve this goal, we will first quantify HGT in a library of bacterial isolates expressing extended spectrum -lactamases (ESBLs). The measured parameters will allow us to expand our models to clinically relevant organisms. We next will integrate modeling and quantitative experiments to define antibiotic dosing and combinations regimes that modulate population dynamics to minimize fraction of resistant organisms and to reverse antibiotic resistance. The proposed research will generate unprecedented, quantitative measurements of modulation of HGT by antibiotics and other environmental factors. The antibiotic dosing strategies will be useful for guiding the use of antibiotics in the clinical setting.